scholarly journals Analysis of Drought-Sensitive Areas and Evolution Patterns through Statistical Simulations of the Indian Ocean Dipole Mode

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1302 ◽  
Author(s):  
Qing-Gang Gao ◽  
Vonevilay Sombutmounvong ◽  
Lihua Xiong ◽  
Joo-Heon Lee ◽  
Jong-Suk Kim
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Diagnostic Techniques ◽  
Eastern Coast ◽  
Indochina Peninsula ◽  
Indian Ocean Dipole Mode ◽  
Sensitive Areas ◽  
The Indian Ocean ◽  
Long Term Trend

In this study, we investigated extreme droughts in the Indochina peninsula and their relationship with the Indian Ocean Dipole (IOD) mode. Areas most vulnerable to drought were analyzed via statistical simulations of the IOD based on historical observations. Results of the long-term trend analysis indicate that areas with increasing spring (March–May) rainfall are mainly distributed along the eastern coast (Vietnam) and the northwestern portions of the Indochina Peninsula (ICP), while Central and Northern Laos and Northern Cambodia have witnessed a reduction in spring rainfall over the past few decades. This trend is similar to that of extreme drought. During positive IOD years, the frequency of extreme droughts was reduced throughout Vietnam and in the southwestern parts of China, while increased drought was observed in Cambodia, Central Laos, and along the coastline adjacent to the Myanmar Sea. Results for negative IOD years were similar to changes observed for positive IOD years; however, the eastern and northern parts of the ICP experienced reduced droughts. In addition, the results of the statistical simulations proposed in this study successfully simulate drought-sensitive areas and evolution patterns of various IOD changes. The results of this study can help improve diagnostic techniques for extreme droughts in the ICP.

scholarly journals Seasonality and Predictability of the Indian Ocean Dipole Mode: ENSO Forcing and Internal Variability

2015 ◽  
Vol 28 (20) ◽  
pp. 8021-8036 ◽  
Author(s):  
Yun Yang ◽  
Shang-Ping Xie ◽  
Lixin Wu ◽  
Yu Kosaka ◽  
Ngar-Cheung Lau ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Internal Variability ◽  
Forced Response ◽  
Sea Surface ◽  
Boreal Summer ◽  
Destructive Interference ◽  
Indian Ocean Basin Mode ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean

Abstract This study evaluates the relative contributions to the Indian Ocean dipole (IOD) mode of interannual variability from the El Niño–Southern Oscillation (ENSO) forcing and ocean–atmosphere feedbacks internal to the Indian Ocean. The ENSO forcing and internal variability is extracted by conducting a 10-member coupled simulation for 1950–2012 where sea surface temperature (SST) is restored to the observed anomalies over the tropical Pacific but interactive with the atmosphere over the rest of the World Ocean. In these experiments, the ensemble mean is due to ENSO forcing and the intermember difference arises from internal variability of the climate system independent of ENSO. These elements contribute one-third and two-thirds of the total IOD variance, respectively. Both types of IOD variability develop into an east–west dipole pattern because of Bjerknes feedback and peak in September–November. The ENSO forced and internal IOD modes differ in several important ways. The forced IOD mode develops in August with a broad meridional pattern and eventually evolves into the Indian Ocean basin mode, while the internal IOD mode grows earlier in June, is more confined to the equator, and decays rapidly after October. The internal IOD mode is more skewed than the ENSO forced response. The destructive interference of ENSO forcing and internal variability can explain early terminating IOD events, referred to as IOD-like perturbations that fail to grow during boreal summer. The results have implications for predictability. Internal variability, as represented by preseason sea surface height anomalies off Sumatra, contributes to predictability considerably. Including this indicator of internal variability, together with ENSO, improves the predictability of IOD.

scholarly journals Satellite and Argo Observed Surface Salinity Variations in the Tropical Indian Ocean and Their Association with the Indian Ocean Dipole Mode

2015 ◽  
Vol 28 (2) ◽  
pp. 695-713 ◽  
Author(s):  
Yan Du ◽  
Yuhong Zhang
Keyword(s):  
Indian Ocean ◽  
Ocean Circulation ◽  
Indian Ocean Dipole ◽  
Coastal Upwelling ◽  
Tropical Indian Ocean ◽  
Sea Surface Salinity ◽  
The South ◽  
Surface Salinity ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean

Abstract This study investigates sea surface salinity (SSS) variations in the tropical Indian Ocean (IO) using the Aquarius/Satelite de Aplicaciones Cientificas-D (SAC-D) and the Soil Moisture and Ocean Salinity (SMOS) satellite data and the Argo observations during July 2010–July 2014. Compared to the Argo observations, the satellite datasets generally provide SSS maps with higher space–time resolution, particularly in the regions where Argo floats are sparse. Both Aquarius and SMOS well captured the SSS variations associated with the Indian Ocean dipole (IOD) mode. Significant SSS changes occurred in the central equatorial IO, along the Java–Sumatra coast, and south of the equatorial IO, due to ocean circulation variations. During the negative IOD events in 2010, 2013, and 2014, westerly wind anomalies strengthened along the equator, weakening coastal upwelling off Java and Sumatra and decreasing SSS. South of the equatorial IO, an anomalous cyclonic gyre changed the tropical circulation, which favored the eastward high-salinity tongue along the equator and the westward low-saline tongue in the south. An upwelling Rossby wave favored the increase of SSS farther to the south. During the positive IOD events in 2011 and 2012, the above-mentioned processes reversed, although the decrease of SSS was weaker in magnitude.

scholarly journals Relationship between Indian Ocean dipole mode and summer monsoon

MAUSAM ◽  
2021 ◽  
Vol 59 (2) ◽  
pp. 167-172
Author(s):  
INDU BALA ◽  
O. P. SINGH
Keyword(s):  
Indian Ocean ◽  
Summer Monsoon ◽  
Indian Ocean Dipole ◽  
Summer Monsoon Rainfall ◽  
Monsoon Onset ◽  
Dipole Mode ◽  
Peninsular India ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean ◽  
Withdrawal Phase

Utilizing the Indian Ocean Dipole Mode (IODM) and Indian Summer Monsoon Rainfall (ISMR) data for the period 1960-2002 the relationships between the IODM and monsoon onset over Kerala and rainfall distribution over the country have been studied. It has been found that stronger/weaker western pole during April-May is associated with delayed/early monsoon onset over Kerala. Stronger eastern pole during March-April seems to be associated with enhanced seasonal (June-September) rainfall over peninsular India. The IODM index of July-August can provide good indications of summer monsoon activity over peninsular India during the withdrawal phase of the  monsoon, i.e., during September.

scholarly journals Improved Prediction of the Indian Ocean Dipole Mode by Use of Subsurface Ocean Observations

2017 ◽  
Vol 30 (19) ◽  
pp. 7953-7970 ◽  
Author(s):  
Takeshi Doi ◽  
Andrea Storto ◽  
Swadhin K. Behera ◽  
Antonio Navarra ◽  
Toshio Yamagata
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Three Dimensional ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Seasonal Prediction ◽  
Dipole Mode ◽  
Indian Ocean Dipole Mode ◽  
Ocean Data Assimilation ◽  
The Indian Ocean

Abstract The numerical seasonal prediction system using the Scale Interaction Experiment–Frontier version 1 (SINTEX-F) ocean–atmosphere coupled model has so far demonstrated a good performance for prediction of the Indian Ocean dipole mode (IOD) despite the fact that the system adopts a relatively simple initialization scheme based on nudging only the sea surface temperature (SST). However, it is to be expected that the system is not sufficient to capture in detail the subsurface oceanic precondition. Therefore, the authors have introduced a new three-dimensional variational ocean data assimilation (3DVAR) method that takes three-dimensional observed ocean temperature and salinity into account. Since the new system has successfully improved IOD predictions, the present study is showing that the ocean observational efforts in the tropical Indian Ocean are decisive for improvement of the IOD predictions and may have a large impact on important socioeconomic activities, particularly in the Indian Ocean rim countries.

scholarly journals Identification of Hotspots of Rainfall Variation Sensitive to Indian Ocean Dipole Mode through Intentional Statistical Simulations

2019 ◽  
Author(s):  
Jong-Suk Kim ◽  
Phetlamphanh Xaiyaseng ◽  
Lihua Xiong ◽  
Sun-Kwon Yoon ◽  
Taesam Lee
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Clear Understanding ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean ◽  
Dry Seasons ◽  
Rainfall Patterns ◽  
Wet And Dry Seasons

Abstract. This study analyzed the sensitivity of rainfall patterns over the Indochina Peninsula (ICP) to sea surface temperature in the Indian Ocean based on statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry seasons to identify hotspots sensitive to ocean warming in the Indo-Pacific sector. Rainfall variability across the ICP was confirmed amplified by combined and/or independent effects of the El Niño–Southern Oscillation and the Indian Ocean Dipole (IOD). During the years of El Niño and a positive phase of the IOD, rainfall is less than usual in Thailand, Cambodia, southern Laos, and Vietnam. Conversely, during the years of La Niña and a negative phase of the IOD, rainfall throughout the ICP is above normal, except in parts of central Laos and northern Vietnam. This study also simulated the change of ICP rainfall in the wet and dry seasons according to intentional IOD changes, and IOD-sensitive hotspots were verified through quantitative analysis. The results of this study provide clear understanding both of the sensitivity of regional precipitation to the IOD and of the potential future impact of statistical changes regarding the IOD in terms of understanding regional impacts associated with precipitation in a changing climate.

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